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15 Cards in this Set

  • Front
  • Back
A population is the complete collection of elements (people, scores, measurements, and so on) to be studied.
Any unknown quantity of the population is referred to as a parameter.
A sample is any subset of elements selected from the population.
Any quantity computed from the sample is called a statistic.
statistical inference
A statistical inference is an estimate or prediction or some other conclusion about a population based on information contained in a sample.
simple random sample
If a sample is taken in such a way that each element in the population has an equal chance of being selected, the resulting sample is called a simple random sample.
cluster sample
A sample is called a cluster sample if a simple random sample of clusters of elements in a population is selected.
systematic sample
A sample obtained in a systematic fashion is called a systematic sample.
two types: quantitative and qualitative
four measurement scales
Nominal Scale- The nominal scale is characterized by data that consist of unordered names, labels, or categories only.
Ordinal Scale- The ordinal scale is characterized by data that consist of ordered categories.
Ratio Scale- Measurements on the ratio scale have meaningful differences and ratios.
Interval Scale
frequency distribution
A frequency distribution (or frequency table) groups data items into classes and then records the number of items that appear in each class.
relative frequency
the frequency divided by the sample size
Adjacent bars representing the (relative) frequency distribution of measurements on the interval or ratio scale are called histograms.
Sample Mean = the sum of all the data values / the number of values in the data set
The sample median, or just median for simplicity, is the middle value of a data set.
The sample mode of a data set is the data value that occurs most frequently in the data set.